Generative AI
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Superintelligence promises incredible advancements and solutions to the world’s biggest challenges, yet it also presents an ominous threat to society. As the lines between innovation and catastrophe blur, understanding the risks of AI is crucial. Read on for recommendations for moving forward in this uncharted territory.
Generative Artificial Intelligence’s emergence has led enterprises, tech vendors, and entrepreneurs to explore many different use cases for this disruptive technology while regulators seek to comprehend its wide-ranging implications and ensure its responsible use. Learn how enterprises can leverage GAI in our webinar, Welcoming the AI Summer: How Generative AI is Transforming Experiences.
Concerns persist as tech visionaries warn that AI might surpass human intelligence by the end of the decade. Humans are still far from fully grasping its potential ramifications and understanding how to collaborate with the technology and effectively mitigate its risks.
In a groundbreaking announcement in July, OpenAI unveiled that it has tasked a dedicated team with creating technologies and frameworks to control AI that surpasses human intelligence. It also committed to dedicating 20% of its computing resources to address this critical issue.
While initially exciting, the prospect of superintelligence also brings numerous challenges and risks. As we venture into this uncharted territory, understanding AI’s evolution and its potential implications on society becomes essential. Let’s explore this further.
AI can be broadly categorized into the following three types:
Narrow AI systems are designed to excel at specific tasks, such as language translation, playing chess, or driving autonomous vehicles. Operating within well-defined boundaries, they cannot transfer knowledge or skills to other domains. Common examples include virtual assistants like Siri and Alexa, recommendation algorithms on streaming platforms, and image recognition software.
General AI possesses human-like cognitive abilities and can perform various intellectual tasks across various domains. Unlike narrow AI, general AI has the potential to learn from experiences and apply knowledge to different scenarios.
Super AI represents a hypothetical AI that surpasses human cognitive abilities in all domains. It holds the promise to solve complex global challenges, such as climate change and disease eradication.
Amidst growing concerns about the risks of superintelligence, the departure of Geoffrey Hinton, known as “the Godfather of AI,” from Google was one of the most significant developments in the AI realm. Hinton is not alone in his concern about AI risks. More than 1,000 tech leaders and researchers have signed an open letter urging a pause in AI development to give the world a chance to adapt and understand the current developments.
These leaders emphasized that development should not be done until we are certain that the outcomes will be beneficial and when the AI risks are fully known and can be managed.
In the letter, they highlighted the following five key AI risks:
As we already have seen some risks associated with this technology materialize, cautiously approaching the advancement of its progress is necessary.
To mitigate AI risks and the risk of superintelligence while promoting its development for positive societal outcomes, we recommend enterprises take the following actions:
While new technologies have always brought changes to the existing norms, disrupted established industries, and transformed societal dynamics, ensuring these advancements are beneficial to a larger audience is essential.
To discuss the risks of Generative AI, its use cases, and its implications across different industries, contact Niraj Agarwal, Priya Bhalla, and Vishal Gupta.
Technology services provider Infosys has announced it is entering into a framework agreement with one of its existing strategic clients to provide artificial intelligence (AI) and automation-led development.
Peter Bendor-Samuel, Chief Executive Officer (CEO) and Founder of Everest Group, shared that all technology services companies – particularly India-based ones – are aggressive about riding the AI wave. “We see a lot of AI washing, provider firms claiming they are doing a lot. However, we believe we are at the start of the wave and most enterprise firms (customers) are still getting organized. We think much of the dialogue from the service provider community is early positioning and posturing,” he adds.
As companies proceed with digital transformation efforts, their focus is firmly on enabling business outcomes with data, increasing demand for data science, analytics, AI, and even RPA skills.
“With the entry of ChatGPT and other generative AI, we expect the demand for data science, AI, and machine learning to further surge in the coming time,” says Aamir Khan, Senior Analyst at Everest Group.
Generative AI (GAI) technology has been around for nearly half a century. But recent developments in the maturity of AI models, faster computation power of systems, and availability of high-quality training data are redefining the technology in 2023.
While tech giants like Microsoft, Google, and Meta fight to dominate the GAI landscape, leading experience providers like Adobe, Salesforce, and Oracle are entering the market with significant investments.
In this on-demand webinar, Everest Group’s experts will highlight the use cases and potential of GAI technology in crafting experiences, its limitations and risks in terms of full-fledged commercial adoption, and the industry’s predicted response.
Our speakers discuss:
Who should attend?
A data strategy outlines how an organization will manage and leverage its data assets to achieve its business objectives. It involves defining the data architecture, governance, management, and analytics practices used to ensure that data is accurate, accessible, and secure.
“I can’t stress this enough: data or the lack of the right data strategy is the number one bottleneck to scaling or doing anything with AI,” said Nitish Mittal, Partner at Everest Group. “When clients come to us with what they think is an AI problem, it is almost always a data problem. AI depends on viable data to prosper. That’s why it’s important to think about the data first.”
Artificial Intelligence (AI), technology integration, and consumerization are among the key trends driving the future of healthcare, a glimpse into the horizon at HIMSS23 showed. Read on to learn takeaways from Everest Group analysts who attended the recent global healthcare conference.
More than 35,000 healthcare leaders converged in Chicago last week to share ideas, highlight investments, showcase demos, and shape the future at HIMSS23. Technology integration, value realization, and risk avoidance dominated conversations at this year’s more strategic and connected conference focused on finding solutions to urgent issues.
Here are the three main themes we saw at HIMSS23:
Integration was a major topic, as many organizations struggle to stitch together various composable platforms. While microservices have enabled precision and faster outcomes for specific use cases, these independent solutions often do not communicate with each other, which can hinder value realization. Many stakeholders we interacted with highlighted the desire to explore ways to better integrate these platforms.
Generative AI, like ChatGPT, and its potential applications is creating a lot of excitement. Major technology companies such as Microsoft and Google are leading the way in developing innovative uses for AI in healthcare, including creating new health applications. While some early examples of AI in healthcare show promise, such as voice dictation that help doctors document patient information more efficiently, how AI will address broader healthcare challenges such as staffing shortages, physician burnout, and rising costs remain to be seen.
Putting the patient at the center of healthcare was another recurring theme, with a focus on designing healthcare systems and technologies that are intuitive and seamless for users. The increased emphasis on user experience has been influenced by the consumer world, where these types of technologies are the norm. The coming years are likely to bring a greater focus on patient portals, wearable health solutions, and virtual care delivery technologies to improve patient/member experience.
The annual HIMSS conference returned to Chicago, with attendees noting a greater sense of urgency and action in meetings versus prior events in Orlando and Las Vegas. A large number of healthcare information and technology companies attending were focused on emerging enterprise priorities around value-based care (VBC) and interoperability.
Leaders engaged in meatier discussions focused on integration, value realization, and risk avoidance. The conversations showed that healthcare enterprises are looking for solutions to get more out of their technology, budgets, and resources in today’s challenging environment.
The large post-pandemic turnout demonstrated the appetite for in-person interaction. Event organizers focused on creating more focused opportunities for attendees to gather and have relaxed and candid conversations with friends, colleagues, and clients, which have been difficult to replicate virtually.
Overall, interacting with industry leaders influencing the next stage in healthcare technology at HIMSS23 was an illuminating experience for Everest Group analysts Abhishek Singh and Manu Aggarwal, who are available to share their insights.
Continue reading about the healthcare industry and the trends influencing decision-making by healthcare payers in our blog, The Recessionary Conundrum: What Lies Ahead for Healthcare Payers?
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